A tremendous gap exists between available culture and animal models and methods that can extract detailed information on cell-cell communication networks governing system responses to perturbations, such as an inflammatory cue. Networks inherently operate in a complex, interlinked fashion, and often exhibit non-intuitive outcomes from intervention at a particular point in the network, as evidenced by failure of many targeted therapeutics to operate in the clinical setting after promising results in currently- available preclinical trials. Cell-cell communication networks comprise factors the cells release into the extracellular milieu (e.g., cytokines, proteases) along with intracellular signals. While an immense amount of effort has focused on intracellular signals generated in simple cell culture systems by straightforward treatment with individual stimulatory cues, it is not clear how relevant those are to the signals arising from interplay of multiple cues being produced at sequential time-points by diverse cell types as dynamic cascades. Elucidating vital aspects of the interplay of extracellular factors in multi-population cellular systems is crucial for understanding tissue pathophysiology but is exceedingly difficult to study in vivo or in traditional cell culture systems. In this project, we will develop transformative new methods to integrate real time molecular probes of cell-cell communication networks and consequent cell behavior into complex, physiological 3D cultures, allowing multiplexed, dynamic information to be derived from these cultures in response to specific manipulations of the system variables, including cell populations involved and external perturbations such as inflammatory cues. Our goal is to build models of primary human systems to serve as close mimics of in vivo complexity, hence we focus on developing new methods that do not rely on genetic manipulation of the cell populations to generate information about systems operation. Our overall project will advance via three parallel but interwoven efforts: development of an analytical formalism for communication modes that connects extracellular and intracellular networks and provides a framework for identifying key extracellular nodes from measurements (such as proteomic analysis) of extracellular medium; development of new biomaterials microenvironments that both control and record key nodes in local cell communication signals in the pericellular environment in a multiplexed manner, with high spatial and temporal resolution; and integration of these approaches into microscale perfused culture systems that foster appropriate cellular and tissue physiology through control of factors including extracellular matrix properties, culture geometry, local oxygen tension, and mechanical stresses. A major innovation in our work is linking these approaches in a synergistic manner to provide systems that can be used broadly in a wide variety of tissue systems with application to an array of individual diseases, including those where sexually dimorphic responses are prominent. PUBLIC HEALTH RELEVANCE: The goal of this project is transform our ability to probe cell-cell communication networks in human cell systems via linking systems biology with tissue engineering. Our overall project will advance via three parallel but interwoven efforts: development of an analytical formalism for communication modes that connects extracellular and intracellular networks and provides a framework for identifying key extracellular nodes from measurements (such as proteomic analysis) of extracellular medium; development of new biomaterials microenvironments that both control and record key nodes in local cell communication signals in the pericellular environment in a multiplexed manner, with high spatial and temporal resolution; and integration of these approaches into microscale perfused culture systems that foster appropriate cellular and tissue physiology through control of factors extracellular matrix properties, culture geometry, local oxygen tension, and mechanical stresses.